Demonstrate a critical understanding of quantitative data analysis and apply appropriate analytical techniques to a range of data using quantitative data analysis software.
2025-01-31 13:56:11
Assessment 1 - Research Proposal (30% of the total mark, 1,050 words)
Task
This is due by Friday the 31st of Jan
For Assignment One, you are required to design a research proposal in your cognate area of specialisation, which is MBA Marketing. In addition note that all dissertation research projects should have an organisational or management focus.
The word count for this specific assessment excludes the references, tables, figures, etc.
You must complete the assessments using hypothetical test data. Hypothetical test data means that you collect the data from your classmates and peers only (not from external individuals). This is a non-random non-probability sampling strategy. For this assessment you will use analysis techniques that are not appropriate for non-random non-probability samples. However in your dissertation you will need to reflect on the most appropriate analysis for your sample. The intention of this assessment is that you will gain the skills that you may need to apply for your dissertation research project. Each individual dissertation research project requires a different approach to analysis. Please speak to your supervisor at that stage if you are unclear.
The analysis and interpretation of the hypothetical test data should be briefly provided and recommendations for further research in the form of a wish-list for successfully implementing a real research project. The intention of this assignment is that it can be used as a trial run to guide you when planning your full dissertation research project.
Please note that a pass for this assessment does not mean that your project has been ‘approved’ in the format you have submitted. It is likely that you will focus your research question following your literature review in ONL723 and/or at the start of your dissertation module. Your project needs to be specific enough to be achievable within the timeframe you have available.
The following additional guidelines will be applicable:
- If you intend to collect secondary numerical data from the Office for National Statistics, Bloomberg, Governments or the International Monetary Fund (for example), then SPSS should be used to analyse the data quantitatively using the regression, correlation analyses or other quantitative tools.
- If you intend to collect primary data from individual peer respondents, such as by conducting interviews or obtaining qualitative data from websites or the internet, then the NVivo software should be employed by using the thematic analysis, storytelling, content analysis or other qualitative tools to explore the data.
- If you intend to collect primary data from individual peer respondents, such as by conducting survey questionnaires, posting the survey online within Canvas and asking for the respondents’ opinions using multiple choice answers, then SPSS should be employed to analyse the data.
- Learning Outcomes Tested in Assessments One (30%) and Two (70%)
1) Demonstrate a critical understanding of quantitative data analysis and apply appropriate analytical techniques to a range of data using quantitative data analysis software. (Assignment Two)
2) Demonstrate a critical understanding of qualitative data analysis and apply appropriate analytical techniques to data using qualitative data analysis software. (Assignment Two)
3) Develop a comprehensive and practicable research proposal which includes a viable research question and supporting aim and objectives. (Assignment One)
4) Design an appropriate research methodology proposing a suitable sampling strategy; data collection approach; valid analytical method(s); associated philosophical stance; and any ethical issues related to the research question. (Assignment One)
Assessment Two - Portfolio (70% of the total mark, 2,450 words, due end of Week 8)
Task
For Assessment Two, you need to collect data and analyse it using the software packages provided such as SPSS, NVivo etc.
Please click here to download Assessment 2Download Please click here to download Assessment 2
This assignment is due on 22nd of Feb 2025
You will need to submit your assignment via Turnitin. Please refer to the orientation module if you are not familiar with this tool.
NOTE
The word count for this specific assessment excludes the references, tables, figures, etc. You must complete the assessments using hypothetical test data. Hypothetical test data means that you collect the data from your classmates and peers only (not from external individuals). Please DO NOT share your survey link with anyone not taking the course.
The analysis and interpretation of the hypothetical test data should be briefly provided and recommendations for further research in the form of a wish-list for successfully implementing a real research project. The intention of this assignment is that it can be used as a trial run to guide you when planning your full dissertation research project.
The following additional guidelines will be applicable:
• If you intend to collect secondary numerical data from the Office for National Statistics, Bloomberg, Governments or the International Monetary Fund (for example), then SPSS should be used to analyse the data quantitatively using the regression, correlation analyses or other quantitative tools.
• If you intend to collect primary data from individual peer respondents, such as by conducting interviews or obtaining qualitative data from websites or the internet, then the NVivo software should be employed by using the thematic analysis, storytelling, content analysis or other qualitative tools to explore the data.
• If you intend to collect primary data from individual peer respondents, such as by conducting survey questionnaires, posting the survey online within Canvas and asking for the respondents’ opinions using multiple choice answers, then SPSS should be employed to analyse the data.
For assignment 2 a few things to consider for assignment 2.
1st - You need to create a survey for assignment 2 which gets posted in section 2.2.2, ideally try and get that done before the assignment 1 hand in, also support your fellow students and complete their surveys as well.
2nd - IMPORTANT - The survey results get discussed in assignment 2 with the aid of specialist software SPSS and NVivio.
3rd - IMPORTANT - SPSS and NVivio only have a 4 week trial period, but you should be able to obtain a student discount to have the software for longer.
Question : Demonstrate a critical understanding of quantitative data analysis and apply appropriate analytical techniques to a range of data using quantitative data analysis software
Answer ( DO NOT COPY ) :
Critical Understanding of Quantitative Data Analysis and Application of Analytical Techniques
Quantitative data analysis is a systematic approach used to examine numerical data through statistical methods to identify patterns, relationships, and trends. It involves the application of mathematical models and statistical tools to interpret data, making it essential in research, business, healthcare, and social sciences.
A critical understanding of quantitative data analysis involves recognizing its key principles, strengths, and limitations. Quantitative research is often structured, objective, and relies on large datasets to ensure generalizability. However, it may not always capture the complexity of human behavior or contextual factors. Therefore, researchers must carefully select appropriate techniques to derive meaningful conclusions.
Application of Analytical Techniques Using Quantitative Data Analysis Software
Quantitative data analysis software, such as SPSS, R, Python, Excel, and Stata, enables researchers to perform complex statistical analyses efficiently. The choice of analytical technique depends on the nature of the data and the research objectives. Some commonly applied techniques include:
- Descriptive Statistics – Used to summarize data through measures such as mean, median, standard deviation, and frequency distributions. This helps provide a clear overview of dataset characteristics.
- Inferential Statistics – Techniques like t-tests, ANOVA, and chi-square tests allow researchers to draw conclusions about a population based on sample data, helping to determine statistical significance.
- Regression Analysis – Used to assess relationships between variables, such as predicting outcomes based on independent variables (e.g., linear and multiple regression models).
- Correlation Analysis – Measures the strength and direction of relationships between two numerical variables (e.g., Pearson’s correlation coefficient).
- Data Visualization – Tools like histograms, scatter plots, and box plots help in presenting data graphically, improving interpretability.
By applying these techniques using statistical software, researchers can efficiently analyze large datasets, minimize errors, and generate accurate, data-driven insights... to be continued!!
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